1. Field of the Invention
This invention relates to methodology for utilizing data mining techniques in the area of regional product allocation management.
2. Introduction to the Invention
Data mining techniques are known and include disparate technologies, like neural networks, which can work to an end of efficiently discovering valuable, non-obvious information from a large collection of data. The data, in turn, may arise in fields ranging from e.g., marketing, finance, manufacturing, or retail.
We have now discovered novel methodology for exploiting the advantages inherent generally in data mining technologies, in the particular field of regional product allocation management applications.
Our work proceeds in the following way.
We have recognized that a typical and important xe2x80x9cthree-partxe2x80x9d paradigm for presently effecting regional product allocation management, is a largely subjective, human paradigm, and therefore exposed to all the vagaries and deficiencies otherwise attendant on human procedures. In particular, the three-part paradigm we have in mind works in the following way. First, a regional product allocation manager develops a demand database comprising a compendium of individual demand historyxe2x80x94e.g., the demand""s response to historical supply situations. Secondly, and independently, the regional product allocation manager develops in his mind a supply database comprising the regional product allocation manager""s personal, partial, and subjective knowledge of objective retail facts culled from e.g., the marketing literature, the business literature, or input from colleagues or salespersons. Thirdly, the regional product allocation manager subjectively correlates in his mind the necessarily incomplete and partial supply database, with the demand database, in order to promulgate an individual""s demand""s prescribed regional product allocation management evaluation and cure.
This three-part paradigm is part science and part art, and captures one aspect of the problems associated with regional product allocation management. However, as suggested above, it is manifestly a subjective paradigm, and therefore open to human vagaries.
We now disclose a novel computer method which can preserve the advantages inherent in this three-part paradigm, while minimizing the incompleteness and attendant subjectivities that otherwise inure in a technique heretofore entirely reserved for human realization.
To this end, in a first aspect of the present invention, we disclose a novel computer method comprising the steps of:
i) providing a demand database comprising a compendium of demand retail history;
ii) providing a supply database comprising a compendium of at least one of regional product allocation management solutions, regional product allocation information, and. regional product allocation diagnostics; and
iii) employing a data mining technique for interrogating said demand and supply databases for generating an output data stream, said output data stream correlating demand problem with supply solution.
The novel method preferably comprises a further step of updating the step i) demand database, so that it can cumulatively track the demand history as it develops over time. For example, this step i) of updating the demand database may include the results of employing the step iii) data mining technique. Also, the method may comprise a step of refining an employed data mining technique in cognizance of pattern changes embedded in each database as a consequence of supply results and updating the demand database.
The novel method preferably comprises a further step of updating the step ii) supply database, so that it can cumulatively track an ever increasing and developing technical regional product allocation management literature. For example, this step ii) of updating the supply database may include the effects of employing a data mining technique on the demand database. Also, the method may comprise a step of refining an employed data mining technique in cognizance of pattern changes embedded in each database as a consequence of supply results and updating the supply database.
The novel method may employ advantageously a wide array of step iii) data mining techniques for interrogating the demand and supply database for generating an output data stream, which output data stream correlates demand problem with supply solution. For example, the data mining technique may comprise inter alia employment of the following functions for producing output data: classification-neural, classification-tree, clustering-geoographic, clustering-neural, factor analysis, or principal component analysis, or expert systems.
In a second aspect of the present invention, we disclose a program storage device readable by machine to perform method steps for providing an interactive regional product allocation management database, the method comprising the steps of:
i) providing a demand database comprising a compendium of individual demand history;
ii) providing a supply database comprising a compendium of at least one of regional product allocation management solutions, regional product allocation information, and regional product allocation diagnostics; and
iii) employing a data mining technique for interrogating said demand and supply databases for generating an output data stream, said output data stream correlating demand problem with supply solution.
In a third aspect of the present invention, we disclose a computer comprising:
i) means for inputting a demand database comprising a compendium of individual demand history;
ii) means for inputting a supply database comprising a compendium of at least one of regional product allocation management solutions, regional product allocation information, and regional product allocation diagnostics;
iii) means for employing a data mining technique for interrogating said supply databases; and
iv) means for generating an output data stream, said output data stream correlating demand problem with supply solution. We have now summarized the invention in several of its aspects or manifestations. It may be observed, in sharp contrast with the prior art discussed above comprising the three part subjective paradigm approach to the problem of product allocation management, that the summarized invention utilizes inter alia, the technique of data mining. We now point out, firstly, that the technique of data mining is of such complexity and utility, that as a technique, in and of itself, it cannot be used in any way as an available candidate solution for enhancing product allocation management, to the extent that the problem of product allocation management is only approached within the realm of the human-subjective solution to product allocation management. Moreover, to the extent that the present invention uses computer techniques including e.g., data mining techniques, to an end of solving a problem of product allocation management, it is not in general obvious within the nominal context of the problem as we have defined it and the technique of data mining, how they are in fact to be brought into relationship in order to provide a pragmatic solution to the problem of product allocation management. It is rather, an aspect of the novelty and unobviousness of the present invention that it discloses, on the one hand, the possibility for using the technique of data mining within the context of product allocation management, and, morever, on the other hand, discloses illustrative methodology that is required to in fact pragmatically bring the technique of data mining to bear on the actuality of solving the problem of product alocation management.
The invention is illustrated in the accompanying drawing, in which
FIG. 1 provides an illustrative flowchart comprehending overall realization of the method of the present invention;
FIG. 2 provides an illustrative flowchart of details comprehended in the FIG. 1 flowchart;
FIG. 3 shows a neural network that may be used in realization of the FIGS. 1 and 2 data mining algorithm; and
FIG. 4 shows further illustrative refinements of the FIG. 3 neural network.